Adaptive object identification and recognition using neural networks and surface signatures

Author

Yamany, Sameh M. ; Farag, Aly A.

Author_Institution

Cairo Univ., Egypt

fYear

2003

fDate

21-22 July 2003

Firstpage

137

Lastpage

142

Abstract

The paper introduces an adaptive technique for 3D object identification and recognition in 3D scanned scenes. This technique uses neural learning of the 3D free-form surface representation of the object in study. This representation scheme captures the 3D curvature information of any free-form surface and encodes it into a 2D image corresponding to a certain point on the surface. This image represents a "surface signature" because it is unique for this point and is independent of the object translation or orientation in space.

Keywords

adaptive signal processing; image registration; image representation; learning (artificial intelligence); neural nets; object recognition; 2D image; 3D object recognition; 3D scanned scenes; adaptive object identification; adaptive object recognition; free-form surface representation; image registration; neural learning; neural networks; surface point signature; surface signatures; Application software; Biomedical computing; Biomedical imaging; Computer vision; Image recognition; Layout; Neural networks; Object recognition; Robot vision systems; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Video and Signal Based Surveillance, 2003. Proceedings. IEEE Conference on

Print_ISBN

0-7695-1971-7

Type

conf

DOI

10.1109/AVSS.2003.1217913

Filename

1217913